Crestal Approach for Maxillary Sinus Augmentation in Patients with ≤4 mm of Residual Alveolar Bone
Bibliographic record
Abstract
PURPOSE: Less morbidity is the major advantage to a one-stage crestal approach to maxillary sinus elevation. However, the ability to ensure high primary implant stability in a severely atrophied ridge is of chief concern. The purpose of this study is to measure and compare the success rate of implants placed at the time of crestal approach sinus lift in patients with ≤ 4 mm of residual alveolar bone (RAB) and >4 mm of RAB. MATERIALS AND METHODS: In this three-site multicenter study, one hundred two patients, 53 males and 49 females, (23-89 years old; mean = 56.2) were evaluated. Three experienced surgeons (>15 years) performed the crestal approach sinus lift microsurgeries with simultaneous implant placement. At baseline and at the follow-up appointments, calibrated examiners measured radiographic interproximal bone level using ImageJ for Windows after calibration of the radiographs. References for the bone level measurements were the platform, first and second threads of the implants. Statistical analyses, using STATA version 12, stratified patients according to RAB height (group 1: RAB of ≤ 4 mm; n = 35 and group 2: RAB > 4 mm; n = 67), age, gender, and treatment center. RESULTS: The success rate was 100% for group 1 and 98.51% for group 2 at 6 to 100 months postprosthetic loading (mean = 29.7 months). The peri-implant bone loss averaged 0.55 mm (interquartile range [IQR] = 0.5 [0-1]) in group 1 and 0.07 mm (IQR = 0 [0-0]) in group 2. There was no statistically significant difference between the two groups. Clinical outcomes were independent of age, gender, and treatment center. CONCLUSIONS: The RAB height did not increase crestal bone loss or reduce the success rate of the implants and associated prostheses. The crestal approach should be considered a viable technique for use in patients with residual bone height of ≤ 4 mm and merits further evaluation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".